%0 Journal Article %1 Chandra2009Computational %A Chandra, Nagasuma %D 2009 %I Expert Opinion %J Expert Opinion on Drug Discovery %K review target-identification %N 12 %P 1221--1236 %R 10.1517/17460440903380422 %T Computational systems approach for drug target discovery %U http://dx.doi.org/10.1517/17460440903380422 %V 4 %X doi: 10.1517/17460440903380422 Importance of the field: The shift in focus from ligand based design approaches to target based discovery over the last two to three decades has been a major milestone in drug discovery research. Currently, it is witnessing another major paradigm shift by leaning towards the holistic systems based approaches rather the reductionist single molecule based methods. The effect of this new trend is likely to be felt strongly in terms of new strategies for therapeutic intervention, new targets individually and in combinations, and design of specific and safer drugs. Computational modeling and simulation form important constituents of new-age biology because they are essential to comprehend the large-scale data generated by high-throughput experiments and to generate hypotheses, which are typically iterated with experimental validation. Areas covered in this review: This review focuses on the repertoire of systems-level computational approaches currently available for target identification. The review starts with a discussion on levels of abstraction of biological systems and describes different modeling methodologies that are available for this purpose. The review then focuses on how such modeling and simulations can be applied for drug target discovery. Finally, it discusses methods for studying other important issues such as understanding targetability, identifying target combinations and predicting drug resistance, and considering them during the target identification stage itself. What the reader will gain: The reader will get an account of the various approaches for target discovery and the need for systems approaches, followed by an overview of the different modeling and simulation approaches that have been developed. An idea of the promise and limitations of the various approaches and perspectives for future development will also be obtained. Take home message: Systems thinking has now come of age enabling a 'bird's eye view' of the biological systems under study, at the same time allowing us to 'zoom in', where necessary, for a detailed description of individual components. A number of different methods available for computational modeling and simulation of biological systems can be used effectively for drug target discovery.

@article{Chandra2009Computational, abstract = {doi: 10.1517/17460440903380422 Importance of the field: The shift in focus from ligand based design approaches to target based discovery over the last two to three decades has been a major milestone in drug discovery research. Currently, it is witnessing another major paradigm shift by leaning towards the holistic systems based approaches rather the reductionist single molecule based methods. The effect of this new trend is likely to be felt strongly in terms of new strategies for therapeutic intervention, new targets individually and in combinations, and design of specific and safer drugs. Computational modeling and simulation form important constituents of new-age biology because they are essential to comprehend the large-scale data generated by high-throughput experiments and to generate hypotheses, which are typically iterated with experimental validation. Areas covered in this review: This review focuses on the repertoire of systems-level computational approaches currently available for target identification. The review starts with a discussion on levels of abstraction of biological systems and describes different modeling methodologies that are available for this purpose. The review then focuses on how such modeling and simulations can be applied for drug target discovery. Finally, it discusses methods for studying other important issues such as understanding targetability, identifying target combinations and predicting drug resistance, and considering them during the target identification stage itself. What the reader will gain: The reader will get an account of the various approaches for target discovery and the need for systems approaches, followed by an overview of the different modeling and simulation approaches that have been developed. An idea of the promise and limitations of the various approaches and perspectives for future development will also be obtained. Take home message: Systems thinking has now come of age enabling a 'bird's eye view' of the biological systems under study, at the same time allowing us to 'zoom in', where necessary, for a detailed description of individual components. A number of different methods available for computational modeling and simulation of biological systems can be used effectively for drug target discovery.}, added-at = {2018-12-02T16:09:07.000+0100}, author = {Chandra, Nagasuma}, biburl = {https://www.bibsonomy.org/bibtex/284726926e8d420e1690a7d37f964ba4e/karthikraman}, citeulike-article-id = {7133906}, citeulike-linkout-0 = {http://dx.doi.org/10.1517/17460440903380422}, citeulike-linkout-1 = {http://www.informahealthcare.com/doi/abs/10.1517/17460440903380422}, day = 1, doi = {10.1517/17460440903380422}, interhash = {ff05f6b87b4046c380751afcf4e27eae}, intrahash = {84726926e8d420e1690a7d37f964ba4e}, journal = {Expert Opinion on Drug Discovery}, keywords = {review target-identification}, month = dec, number = 12, pages = {1221--1236}, posted-at = {2010-05-07 08:56:58}, priority = {2}, publisher = {Expert Opinion}, timestamp = {2018-12-02T16:09:07.000+0100}, title = {Computational systems approach for drug target discovery}, url = {http://dx.doi.org/10.1517/17460440903380422}, volume = 4, year = 2009 }